Some of the material is from the coursework through the program, others from outside sources.
def learn_deep():
return knowledge
Covers Spark, Spark storage, working with RDD, pyspark, map-reduce framework and implementations. Focuses on ETL across different partitions.
Part of the evening course taught by Jeremy Howard. Starts with CNN and works backwards through the deeper parts of neural networks.
Deep dives into Random Forests + Neural Networks, learn how they work, learn to build them from scratch. Explore the use of sklearn and torch flexible libraries for a number of applications
This is still a work in progress, but its basically a written form of the Andrew Ng. Coursera course.